Multimodal Imaging Brain Markers in Early Adolescence Are Linked with a Physically Active Lifestyle
Journal article
Salvan P. et al, (2021), The Journal of Neuroscience, 41, 1092 - 1104
The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants.
Journal article
Fitzgibbon SP. et al, (2020), Neuroimage, 223
Modelling subject variability in the spatial and temporal characteristics of functional modes.
Journal article
Harrison SJ. et al, (2020), Neuroimage, 222
Detecting connectivity in EEG: A comparative study of data-driven effective connectivity measures.
Journal article
Bakhshayesh H. et al, (2019), Comput Biol Med, 111
Detecting synchrony in EEG: A comparative study of functional connectivity measures.
Journal article
Bakhshayesh H. et al, (2019), Comput Biol Med, 105, 1 - 15
Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants
Journal article
Baxter L. et al, (2019), NeuroImage, 186, 286 - 300
Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project
Journal article
Bastiani M. et al, (2019), NeuroImage, 185, 750 - 763
Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction
Journal article
Bastiani M. et al, (2019), NeuroImage, 184, 801 - 812
Construction of a neonatal cortical surface atlas using Multimodal Surface Matching in the Developing Human Connectome Project
Journal article
Bozek J. et al, (2018), NeuroImage, 179, 11 - 29
The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction
Journal article
Makropoulos A. et al, (2018), NeuroImage, 173, 88 - 112
Improved artefact removal from EEG using Canonical Correlation Analysis and spectral slope
Journal article
Janani AS. et al, (2018), Journal of Neuroscience Methods, 298, 1 - 15
Towards Detecting Connectivity in EEG: A Comparative Study of Parameters of Effective Connectivity Measures on Simulated Data
Conference paper
Bakhshayesh H. et al, (2018), 2018 IEEE-EMBS CONFERENCE ON BIOMEDICAL ENGINEERING AND SCIENCES (IECBES), 297 - 301
Evaluation of a minimum-norm based beamforming technique, sLORETA, for reducing tonic muscle contamination of EEG at sensor level
Journal article
Janani AS. et al, (2017), Journal of Neuroscience Methods, 288, 17 - 28
Hand classification of fMRI ICA noise components
Journal article
Griffanti L. et al, (2017), NeuroImage, 154, 188 - 205
Reducing training requirements through evolutionary based dimension reduction and subject transfer
Journal article
Atyabi A. et al, (2017), Neurocomputing, 224, 19 - 36
Electroencephalographic correlates of states of concentrative meditation
Journal article
DeLosAngeles D. et al, (2016), International Journal of Psychophysiology, 110, 27 - 39
Construction of a neonatal cortical surface atlas using multimodal surface matching
Poster
Bozek J. et al, (2016), 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)
Automatic determination of EMG-contaminated components and validation of independent component analysis using EEG during pharmacologic paralysis
Journal article
Fitzgibbon SP. et al, (2016), Clinical Neurophysiology, 127, 1781 - 1793
Cross subject mental work load classification from electroencephalographic signals with automatic artifact rejection and muscle pruning
Conference paper
Kunjan S. et al, (2016), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9919 LNAI, 295 - 303
Cross Subject Mental Work Load Classification from Electroencephalographic Signals with Automatic Artifact Rejection and Muscle Pruning
Conference paper
Kunjan S. et al, (2016), 295 - 303